# Makie | ComputeGraph code example?
**URL:** https://discourse.julialang.org/t/makie-computegraph-code-example/137629
**Category:** Visualization
**Tags:** question, makie, glmakie
**Created:** [June 15, 2026, 2:15am UTC](https://discourse.julialang.org/t/makie-computegraph-code-example/137629 "2026-06-15T02:15:17Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@Audrius-St](https://discourse.julialang.org/u/Audrius-St)
#### Post date: [June 15, 2026, 2:15am UTC](https://discourse.julialang.org/t/makie-computegraph-code-example/137629/1 "2026-06-15T02:15:17Z")
Hello,
Having read the [Makie ComputeGraph documentation](https://docs.makie.org/dev/explanations/compute-pipeline#Connecting-multiple-Compute-Graphs) I find it a bit abstract for me to understand without a worked example.
Searching through Julia Discourse I only found only found a few inconclusive discussions that did not provide much insight.
If someone has figured out how to use ComputeGraph I would appreciate it if they could show me how convert the following MWE to ComputeGraph for the plot, sliders, and toggles
```julia-auto
using GLMakie
using Random
function test_lscene()
f = Figure()
n_rows = 10
n_cols = 10
n_slcs = 10
axs_1 = LScene(
f[1, 1:3],
scenekw = (;
aspect = :data,
backgroundcolor = :white,
camera = cam3d!,
center = true,
clear = true,
raw = false
)
)
x = LinRange(1, n_rows, n_rows)
y = LinRange(1, n_cols, n_cols)
z = LinRange(1, n_slcs, n_slcs)
alpha = 0.7
plt_1 = volumeslices!(
axs_1,
x, y, z,
randn(5 * n_rows, 5 * n_cols, 5 * n_slcs),
alpha = alpha,
bbox_visible = true,
colormap = :thermal,
lowclip = :transparent,
space = :data,
transparency = true
)
# Sliders
dspl_sldr_grid = SliderGrid(
f[2, 2],
(label = "Sagittal - yz plane", range = 1:length(x)),
(label = "Coronal - xz plane", range = 1:length(y)),
(label = "Axial - xy plane", range = 1:length(z)),
)
dspl_sldr_layout = dspl_sldr_grid.layout
dspl_sldr_n_cols = ncols(dspl_sldr_layout)
# Connect sliders to volumeslices! update methods
dspl_sl_yz, dspl_sl_xz, dspl_sl_xy = dspl_sldr_grid.sliders
# Sagittal slider
on(dspl_sl_yz.value) do v;
plt_1[:update_yz][](v)
end
# Coronal slider
on(dspl_sl_xz.value) do v;
plt_1[:update_xz][](v)
end
# Axial slider
on(dspl_sl_xy.value) do v;
plt_1[:update_xy][](v)
end
set_close_to!(dspl_sl_yz, .5length(x))
set_close_to!(dspl_sl_xz, .5length(y))
set_close_to!(dspl_sl_xy, .5length(z))
# Toggles
# Add toggles to show/hide heatmaps
hmap_1 = [plt_1[Symbol(:heatmap_, s)][] for s ∈ (:yz, :xz, :xy)]
toggles_dspl = [Toggle(dspl_sldr_layout[i, dspl_sldr_n_cols + 1], active = true) for i ∈ 1:length(hmap_1)]
map(zip(hmap_1, toggles_dspl)) do (h, t)
on(t.active) do active
h.visible = active
end
end
resize_to_layout!(f)
wait(display(f))
end
function main()
test_lscene()
end
begin
main()
end
```
---
### Author:  [@technocrat](https://discourse.julialang.org/u/technocrat)
#### Post date: [June 15, 2026, 3:33pm UTC](https://discourse.julialang.org/t/makie-computegraph-code-example/137629/2 "2026-06-15T15:33:08Z")
> [@Audrius-St](#):
>
> ComputeGraph for the plot, sliders, and toggles
ComputeGraph in Makie is primarily an internal mechanism for defining custom plot recipes. It describes how a plot type’s input attributes flow through computation stages to produce rendered output. It’s not the idiomatic tool for wiring up UI interactions like sliders and toggles. If you were writing a new `@recipe` macro-defined plot type and needed to declare how input observables are transformed into plotting primitives, which is where Makie’s `ComputeGraph` infrastructure lives, then you’d be looking at the right use case.
In the MWE, consider the making data flow more declarative by replacing some `on()` callbacks with `@lift` / `map` where you’re deriving an observable from another. Instead of on() + imperative mutation, lift where you derive values (not applicable to update\_yz since it’s a side-effectful call, not a derived value), For the toggles
```julia-auto
# More idiomatic to directly connect observable to attribute
map(zip(hmap_1, toggles_dspl)) do (h, t)
connect!(h.visible, t.active) # instead of on() + assignment
end
```
So, for wiring plots to the UI, you’re already using the right approach.
---
### Author:  [@Audrius-St](https://discourse.julialang.org/u/Audrius-St)
#### Post date: [June 15, 2026, 6:00pm UTC](https://discourse.julialang.org/t/makie-computegraph-code-example/137629/3 "2026-06-15T18:00:25Z")
Thank you for your explanation.
Regarding the toggles, I replaced the current toggle code
```julia-auto
map(zip(hmap_1, toggles_dspl)) do (h, t)
on(t.active) do active
h.visible = active
end
end
```
with your suggested code
```julia-auto
map(zip(hmap_1, toggles_dspl)) do (h, t)
connect!(h.visible, t.active)
end
```
which generated the following error message when run:
```julia-auto
julia> include("test_LScene_3D.jl")
ERROR: LoadError: MethodError: no method matching connect!(::ComputePipeline.Computed, ::Observable{Any})
The function `connect!` exists, but no method is defined for this combination of argument types.
Closest candidates are:
connect!(::Observables.AbstractObservable, ::Observables.AbstractObservable)
@ Observables C:\Users\Audrius Stundzia\.julia\packages\Observables\YdEbO\src\Observables.jl:545
connect!(::Transformation, ::Transformation; connect_func, connect_model)
@ Makie C:\Users\Audrius Stundzia\.julia\packages\Makie\WKgwk\src\layouting\transformation.jl:16
```
The issue seems to be that `t.active` is an Observable, whereas `h.visible` is not: `typeof(h.visible) = ComputePipeline.Computed`
In the case of the sliders, wrapping their values as Observables seems straightforward:
```julia-auto
dspl_sl_yz_obs = Observable(dspl_sl_yz.value)
# Etc.
# Sagittal slider
on(to_value(dspl_sl_yz_obs)) do v;
plt_1[:update_yz][](v)
end
# Etc.
```
and works.